Hey mates! A few months ago, I was working on a project that required RTOS for ARM Cortex M3. Long story short, we ended up using the LPC1347 and the RTX RTOS
The problem was that, by that time, there was no port of that operating system or example code to run on LPCExpresso IDE.
I bet that you are thinking:
(if you are actually understanding what I am talking about) Why are you using LPCExpresso when you can use other IDEs like IAR and solve that problem?
The thing is: I was using Linux. And not an average Linux. I had the brilliant idea to try the unstable Ubuntu 13.10 (that just got released by that time). The only IDE that was available for that OS was LPCExpresso (former CodeRed).
In order to make the OS work properly, I had to modify some of the main source code and also make some compiler configurations/ set some flags.
By the time I had to made this, there was no other solution available for this. So, in the case you had the same problem that I had, let me save you some time and provide you with this solution ;)
LPC1347: Download of the project here.
LPC1343: Download of the project here.
Hey fellows! I know that quite a decent amount of time has passed since my last post here. I have, however, a really good excuse for it ;)
No, no, I didn’t quit with Big Data, neither stopped with Embedded Systems (to be sincere, I’ve been working a lot with the second in the last past month). Actually, I spent all this time doing researches and publishing a brand new Big Data project! I used it as my graduation thesis and is all about using MapReduce to process CT images to detect lung nodules.
Yes! How about the doctors use the Big Data strengths to help in the diagnostics of the deadliest Cancer in US?
It’s all about my work :)
I’ll describe it in more details later. If you want to check it, the document (in Portuguese – but with an English abstract) is available here.
The project itself is going to be available in my GitHub soon, and when I get I’ll post the links here too!
See you guys in a bit!
The gitHub links are here. Soon I will write a post getting into more details about how it works.
MatLung: A matlab script that shows the image processing features of the distributed software.
LungProcessor: A single machine program that is fully-code-compatible with the distributed hadoop application. Used for Hadoop code debugging.
LungPostProcessor: The Image metadata post-processor. Used to detect the lung nodules and remove false positives.
LungPostProcessor: The Hadoop image processing application